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We develop a scaling model to estimate U.S. Supreme Court opinion locations and justice ideal points along a common spatial dimension using data derived from the citations between opinions. Citations from new opinions to precedent opinions usually apply and endorse the doctrine of the precedent opinion; however, sometimes they implicitly or explicitly dispute the precedent opinion. We collect original datasets classifying citations from search and seizure and freedom of religion opinions written between 1953 and 2006 into these different types and develop a model relating the similarity of the doctrine embodied in the citing and cited opinions to the relative probability of these different types of citations. The resulting spatial estimates of opinion location are used to evaluate theories of Supreme Court bargaining and opinion writing. We find empirical support for theoretical models that predict the majority opinion will fall at the ideal point of the median member of the majority coalition. Given the centrality of theories of judicial policymaking to various substantive problems in political science, the method of scaling opinions developed in this article can facilitate a range of future research.